Time-Varying Covariates and Semi-Parametric Regression in Capture–Recapture: An Adaptive Spline Approach
Time-Varying Covariates and Semi-Parametric Regression in Capture–Recapture: An Adaptive Spline Approach
复制标题
捕获-重新捕获中的时变协变量和半参数回归：自适应样条方法
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
C. Schwarz
中科院分区：
文献类型：
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作者：
S. Bonner;D. Thomson;C. Schwarz
捕获-再捕获方法的进步已经允许将连续的、时间相关的个体协变量作为生存和捕获概率的预测因子。这些协变量带来的问题是，只有当一个个体被捕获时，它们才会被观察到。一种解决方案是假设一个协变量模型，该模型以观测值为条件，定义未观测值的分布，并应用贝叶斯方法计算参数估计并检验协变量的影响。
Advances in capture–recapture methodology have allowed the inclusion of continuous, time-dependent individual-covariates as predictors of survival and capture probabilities. The problem posed by these covariates is that they are only observed for an individual when that individual is captured. One solution is to assume a model of the covariate which defines the distribution of unobserved values, conditional on the observed values, and apply Bayesian methods to compute parameter estimates and to test the covariate’s effect.